Entity Framework Core Performance Optimization Strategies for High-Throughput Financial Data Systems
DOI:
https://doi.org/10.63282/3117-5481/AIJCST-V4I1P109Keywords:
Entity Framework (EF) Core, .NET, Performance Optimization, Financial Systems, Data Access, Query Optimization, Dapper, Database Performance, High Throughput, Enterprise ApplicationsAbstract
Entity Framework Core is widely adopted for data access in .NET enterprise applications, yet its default behaviors introduce performance bottlenecks that become critical in high-throughput financial data systems processing large transaction volumes. This paper systematically evaluates Entity Framework Core performance optimization strategies including query compilation caching, no-tracking queries, explicit loading versus eager loading tradeoffs, bulk operation handling, and connection pooling configurations in financial services contexts. Benchmarks conducted on representative financial transaction datasets quantify the performance impact of each strategy and identify optimization combinations that yield the greatest throughput improvements. The paper further analyzes when Dapper should supplement or replace Entity Framework Core for performance-sensitive financial data access paths.
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